What this category's data looks like
Data sources for industrial park research reports include official announcements from national or provincial industrial park management committees, monthly operation briefings from park operating entities, and research compilations from industry associations. Two update cadence types apply. Routine operation data is updated monthly. Emergency information such as major investment promotions or policy adjustments is released immediately. Special in-depth research reports are updated quarterly or semi-annually. Typical document structure includes park location overview, list of settled enterprises, revenue and tax data, investment promotion policies, and land usage details. Core fields include number of settled enterprises, tax per mu, contracted investment amount, and some fields have specific units.
What constraints do these characteristics impose during model access and configuration?
The presence of multiple fields with specific units requires enabling structured field extraction during configuration, to prevent the model from confusing units of different metrics. The wide range of document lengths requires setting adaptive segmentation parameters, to accommodate briefings of thousands of characters and in-depth reports of tens of thousands of characters. The large differences in update frequencies require configuring pull rules that distinguish between routine data and emergency data, to avoid mismatches between synchronization frequency and data update cadence. Some data includes non-standardized policy text, requiring configuring an appropriate number of recalled passages to ensure core policy content is fully retrieved.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 1000–2000 characters | Industrial park research reports contain large volumes of structured tables and policy text. This segmentation length preserves semantic integrity while adapting to most models' context windows |
RECALL_TOP_N | Top 8–12 results | Core information in industrial park research reports is scattered across multiple passages. Retrieving a sufficient number of segments covers key metrics and policy content |
reRankTopN | Top 4–6 results | Reranking retains the most relevant core data, avoiding redundant content that could interfere with the model's accurate matching of park metrics |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Single in-depth park research reports contain multi-page tables and long text. This timeout setting ensures complete parsing |
structured_extract_fields | Number of settled enterprises, tax per mu, contracted investment amount | The core decision-making metrics for industrial park research reports are the above fields, which require precise extraction for question-and-answer matching |
SYNC_INTERVAL | 2:00 AM daily | Routine park operation data is updated daily. Synchronizing during early morning avoids peak business hours and ensures data timeliness |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Each scenario requires individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: After enabling the reranking model, the returned recall results only contain 1 passage. Cause: The
reRankTopNparameter was not configured correctly, with a value set to 1. This results in only the single highest-similarity result after reranking being retained. - Phenomenon: A
408 Request Timeouterror occurs when parsing large industrial park research reports. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter is set too short, failing to reserve sufficient time for parsing in-depth reports containing multi-page tables. - Phenomenon: Land units for parks cannot be recognized when calling tools, and extracted tax per mu data contains errors. Cause: Parsing rules for unitized metrics were not configured. The model cannot distinguish the meaning of metrics with different units, leading to field matching deviations.
How to confirm the configuration is complete
- Upload a single typical park operation briefing and in-depth research report, then review the parsed segmentation results. Confirm that segments conform to document semantic splitting requirements.
- Submit a query that includes core park metrics, then review the number of recalled and reranked results. Confirm that the configured recall and reranking parameters cover the required information.
- Trigger a scheduled synchronization task, then review the data update time in the synchronization logs. Confirm that the synchronization cycle matches the update cadence of park data.
- Call the structured extraction interface, then verify that the returned fields include the preset core park metrics. Confirm that the structured extraction configuration is active.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.